The Decision Maker

Consumers, particularly millennials, are becoming less interested in meeting actual people to solve their problems and more interested in doing it themselves. With the rise of the internet, information is readily available to all. This allows consumers to search and find solutions to meet their needs in a matter of seconds. This is a tremendous opportunity for consumers but it is also a serious challenge for retail institutions. This is especially true for retail financial institutions such as community banks and credit unions.

Branches will become increasing less important as more users begin to use their mobile devices for their banking needs. The demise of branches results in the demise of physical relationships. Traditionally, retail financial institutions have generated new sales by interacting with their members when they come into the branch. By building relationships, credit union employees can help members become financial successful by proposing solutions (new products). The introduction of mobile is threatening this “old way” of building relationships.

Data – The “New Way”

With the loss of face-to-face encounters, credit unions need to find a new way to get to know their members. This is only possible through the use of data analytics. With data analytics, credit unions have the power to “know” their members without actually interacting with them in person. Every time a member makes a transaction, more information is created about their behavior. This transactional behavior creates a unqiue identity for the member.

Building Virtual Relationships

Building relationship through data allows credit unions to gain member loyalty without physically interacting with them. Data enables credit unions to predict member behavior and better serve their financial needs. Unique transactional data helps identify a member’s needs and reveals information about them that has traditionally been skewed by outdated scoring techniques, such as credit scores.

Consider this example from a recent Filene whitepaper:

Simple member behavior, such as which restaurants, grocery stores, and coffee shops members frequent, can predict their credit score. The figure shows different credit score predictions for different stores. For example, members who frequent the British Butcher Shoppe very likely have a credit score of around 800. Members who shop at Save-On-Foods, on the other hand, very likely have a credit score of around 600. The prediction accuracy is given as a score, with 1 representing the highest prediction accuracy for a certain store and 20 the lowest prediction accuracy in an out-of-sample test.

This information enables credit unions to ease their lending standards by leveraging other data. A member that would typically be denied a loan or face high interest rates may actually be better qualified. By using transactional data, credit unions can better serve their members by giving them better products and services.

The Threat

Big Data and Analytics is driving a new breed of analytic competitors (e.g. Lending Clubs, Google Wallet, Apple Pay, etc.) into the financial services marketplace. These new entrants are interested in skimming the profitable, information rich, transaction side of the business while leaving the less profitable and highly regulated settlement side to the banks and credit unions. These new competitors have realized that data is the new way to attract and retain customers and are beginning to steal market share from retail financial institutions stuck in their old ways.

The Opportunity

As more members use mobile device for their banking needs, physical branches will become less important. The institution the can provide the most accurate and timely information will prevail. Luckily for credit unions, they already have a wealth of data about their members. This gives them a tremendous advantage over new competitors that are just starting to enter the market place. Unfortunately for credit unions are seriously lagging other industries (e.g. - retail) when it comes to the use of Big Data and Analytics to better serve members.